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Deep Learning

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/pnavarre/esr

공식 코드

edge-SR: Super-Resolution For The Masses

https://github.com/poloclub/cnn-explainer

공식 코드

CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization

https://github.com/poloclub/ganlab

공식 코드

GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation

https://github.com/poloclub/interactive-classification

공식 코드

Interactive Classification for Deep Learning Interpretation

https://github.com/pphub-hy/torch-tapnet

공식 코드

Deep Learning based Intelligent Coin-tap Test for Defect Recognition

https://github.com/ppope/dimensions

공식 코드

The Intrinsic Dimension of Images and Its Impact on Learning

https://github.com/prathmeshrmadhu/recognize_characters_art_history

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Recognizing Characters in Art History Using Deep Learning

https://github.com/pratikpv/malware_detect2

공식 코드

An Empirical Analysis of Image-Based Learning Techniques for Malware Classification

https://github.com/predict-idlab/sleep-linear

공식 코드

Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring

https://github.com/predictiveintelligencelab/actnet

공식 코드

Deep Learning Alternatives of the Kolmogorov Superposition Theorem

https://github.com/predictiveintelligencelab/jaxpi

공식 코드

PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks

https://github.com/preetum/deep-bootstrap-code

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The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers

https://github.com/prev/progressivenet

공식 코드

Progressive Transmission and Inference of Deep Learning Models

https://github.com/privacytrustlab/ml_privacy_meter

공식 코드

Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

https://github.com/profjsb/deepCR

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deepCR: Cosmic Ray Rejection with Deep Learning

https://github.com/project-monai/research-contributions

공식 코드

Open-Source Skull Reconstruction with MONAI

https://github.com/provostultrasoundlab/sparsetensorulm

공식 코드

Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopy

https://github.com/prs-eth/film-ensemble

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FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation

https://github.com/psc-g/Psc2

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Performing Structured Improvisations with pre-trained Deep Learning Models

https://github.com/psu-efd/surrogate_modeling_swes

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Surrogate Model for Shallow Water Equations Solvers with Deep Learning

https://github.com/ptarling/DeepLearningFishCounting

공식 코드

Deep learning with self-supervision and uncertainty regularization to count fish in underwater images

https://github.com/ptkin/Awesome-Super-Resolution

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Deep Learning for Image Super-resolution: A Survey

https://github.com/publioelon/leaf-diseases-classification

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An Edge Computing-Based Solution for Real-Time Leaf Disease Classification using Thermal Imaging

https://github.com/puhsu/tabular-dl-pretrain-objectives

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Revisiting Pretraining Objectives for Tabular Deep Learning

https://github.com/punyajoy/DE-LIMIT

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Deep Learning Models for Multilingual Hate Speech Detection

https://github.com/purduedualitylab/peatmoss-demos

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PeaTMOSS: Mining Pre-Trained Models in Open-Source Software

https://github.com/pyg-team/pytorch-frame

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PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning

https://github.com/pyt-team/TopoBenchmarkX

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TopoBench: A Framework for Benchmarking Topological Deep Learning

https://github.com/pyt-team/topoembedx

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Topological Deep Learning: Going Beyond Graph Data

https://github.com/pyt-team/topomodelx

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Topological Deep Learning: Going Beyond Graph Data

https://github.com/pyt-team/toponetx

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Topological Deep Learning: Going Beyond Graph Data

https://github.com/pytorch/fbgemm

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FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference

https://github.com/pytorch/pytorch

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PyTorch: An Imperative Style, High-Performance Deep Learning Library

https://github.com/qile2000/LAMDA-TALENT

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A Closer Look at Deep Learning Methods on Tabular Datasets

https://github.com/qinfengsama/compressor-based-crop-mapping

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Low-Resource Crop Classification from Multi-Spectral Time Series Using Lossless Compressors

https://github.com/qinnzou/Gait-Recognition-Using-Smartphones

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Deep Learning-Based Gait Recognition Using Smartphones in the Wild

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